Competitive ability and defoliation tolerance in Stipa clarazii, Stipa tenuis y Stipa ambigua

Mayores valores de tasas de crecimiento, capacidad de proliferación radical, densidad de longitud de raíces y capacidad de absorción de nutrientes se han asociado con un aumento en la adquisición de nutrientes en las gramíneas perennes, y contribuirían por ello a su capacidad competitiva y tolerancia a la defoliación (Bedunah y Sosbee, 1995).Fil: Saint Pierre, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; ArgentinaFil: Busso, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; Argentin

Changes in grain quality and grain protein composition of winter wheat cultivars under different levels of soil nitrogen and water stress

Hard white winter (HVVW) wheat cultivars must have superior protein quality and consistent processing quality to be successful in the Asian market. New cultivars and management strategies are needed to produce HVVW grain for both bread and noodle applications from diverse environments in the US Pacific Northwest (PNW). This study investigated the variability in grain quality, grain protein content and composition, and dough mixing properties in relation to moisture stress during grain-fill and nitrogen management in the PNW. Seven HWW and two soft white winter wheats were grown under line source irrigation and two nitrogen fertilization levels over two years and two locations. Plots were irrigated during grain-fill to replace from 100 to less than 30 % of measured evapotranspiration. Grain quality, protein quality, and protein composition were characterized by nitrogen determinations, single kernel analysis, polyphenol oxidase activity (PPO), SDS sedimentation tests, Mixograph analyses, and sizeexclusion HPLC. Water stress during grain-fill negatively affected grain yield, test weight, and kernel weight and diameter. Among HVVW cultivars, water stress caused reductions in test weight which were of larger magnitude in late maturing cultivars than in early genotypes. Mixograph peak time, stability, and tolerance were relatively unchanged over irrigation treatments. Nitrogen fertilization showed a positive contribution to both protein quantity and quality, without affecting PPO levels. Moreover, no significant correlation was found between flour protein and PPO. Changes in protein quality and composition were related to general increases in protein concentration, regardless if the result of reducing irrigation or increasing fertilization. The proportion of monomeric proteins (gliadins) increased more rapidly than the polymeric proteins (glutenins) as flour protein increased. Grouping of genotypes in biplots indicated that cultivars of similar quality responded similarly to treatment combinations in terms of protein quality and dough mixing properties. The patterns of response suggest that management strategies to meet target protein content and enduse quality are relatively independent of genotypic differences. Similar management strategies could then be recommended for HVVW when targeting specific end-uses. Early maturity reduced the impact of water and heat stress during grain-fill and would contribute to enhance grain quality and consistency in PNW cultivars

Peptide labeling with metals using MS detection and optimization of metalloprotein extraction procedures in biological samples with proteomic purposes

Ce travail a développé une nouvelle méthode pour l'identification et la quantification des peptides, par l'optimisation de certaines stratégies disponibles appropriées pour le marquage des peptides avec des métaux lanthanide, une séparation par nano-HPLC et détection UV, et suivi par MALDI MS. Tout d'abord, les peptides ont été marqués avec les trois métaux lanthanides différents et un réactif fonctionnel - DOTA. Les résultats montrent que la réaction de transformation en dérivé à l'aide du réactif chélateur DOTA-NHS-ester a été efficace pour des peptides individuels et des mélanges de peptides, vérifiées à partir de la relation m/z obtenue par MALDI MS. L'application optimisée d un complexe (Cytochrome C digest) a montré des résultats comparables à ceux obtenus avec des peptides modèles. En parallèle, nous avons effectué l optimisation pour la purification de métalloprotéine dans la bile de poisson, qui est signalée entant que biomarqueurs de contamination métallique de l'environnement. Des procédures différentes (différents moments de centrifugation et différentes températures de traitement thermique) et les agents (DTT, b-mercaptoéthanol et TCEP) réduisant ont été apliqués pour purifier les MT isolées de la bile et du foie des poissons (Oreochromis niloticus). Des analyses spectrophotométriques ont été utilisées pour quantifier les échantillons de MT, et le gel SDS-PAGE a été utilisé pour évaluer qualitativement les différents résultats de la procédure. Chaque procédure a en suíte été évaluée statistiquement, une méhtode des surfaces de réponse a été appliquée. Les MT de la bile semblent être plus adéquate pour la surveillance de l'environnement en ce qui concerne l'exposition récente à des xénobiotiques qui peuvent influer sur l'expression protéomique et metalloproteomique de cette matrice biologique. Une procédure d exposition à des métaux dans le laboratoire a montré que les métaux étaient significativement importante pour l évaluation de la contamination à partir de la quantification de MT, selon le traitement de données par une techinique de réseau neural.This work developed a new method for the identification and quantification of peptides, by optimizing some of the available strategies suitable for labeling peptides with lanthanide metals with subsequent separation by nano-HPLC with UV detection, matrix-assisted laser desorption ionization-mass spectrometry (MALDI MS). First, peptides were labeled with the three different lanthanide metals using a functional DOTA-based reagent. The results demonstrate that the derivatization reaction using the chelating reagent DOTA-NHS-ester was effective for single peptides and peptide mixtures, verified from the m/z relation obtained by MALDI MS. The application of the optimized method in a more complex matrix (Cytochrome C digest) showed results comparable to those obtained with model peptides. In parallel, environmental analyses were conducted, by performing the standardization of metalloprotein purification in fish bile, since this matrix has been reported as a biomarker for environmental metal contamination. Different procedures (varying centrifugation times and heat-treatment temperatures) and reducing agents (DTT, b-mercaptoethanol and TCEP) were applied to purify MT isolated from fish (Oreochromis niloticus) bile and liver. Spectrophotometrical analyses were used to quantify the resulting MT samples, and SDS-PAGE gels were used to qualitatively assess the different procedure results. Each procedure was then statistically evaluated. A response surface methodology was applied for bile samples, in order to further evaluate the responses for this matrix. In an environmental context, biliary MT was lower than liver MT, and, bile MT seems to be more adequate in environmental monitoring scopes regarding recent exposure to xenobiotics that may affect the proteomic and metalloproteomic expression of this biological matrix. A procedure for exposure to metals in the laboratory showed that some metals are significantly important for the assessment of contamination from the quantification of MT, according to the data processing by atifical neural network (ANN).PAU-BU Sciences (644452103) / SudocSudocFranceF

Linkage disequilibrium patterns, population structure and diversity analysis in a worldwide durum wheat collection including Argentinian genotypes

Background: Durum wheat (Triticum turgidum L. ssp. durum Desf. Husn) is the main staple crop used to make pasta products worldwide. Under the current climate change scenarios, genetic variability within a crop plays a crucial role in the successful release of new varieties with high yields and wide crop adaptation. In this study we evaluated a durum wheat collection consisting of 197 genotypes that mainly comprised a historical set of Argentinian germplasm but also included worldwide accessions. Results: We assessed the genetic diversity, population structure and linkage disequilibrium (LD) patterns in this collection using a 35 K SNP array. The level of polymorphism was considered, taking account of the frequent and rare allelic variants. A total of 1547 polymorphic SNPs was located within annotated genes. Genetic diversity in the germplasm collection increased slightly from 1915 to 2010. However, a reduction in genetic diversity using SNPs with rare allelic variants was observed after 1979. However, larger numbers of rare private alleles were observed in the 2000–2009 period, indicating that a high reservoir of rare alleles is still present among the recent germplasm in a very low frequency. The percentage of pairwise loci in LD in the durum genome was low (13.4%) in our collection. Overall LD and the high (r2 > 0.7) or complete (r2 = 1) LD presented different patterns in the chromosomes. The LD increased over three main breeding periods (1915–1979, 1980–1999 and 2000–2020). Conclusions: Our results suggest that breeding and selection have impacted differently on the A and B genomes, particularly on chromosome 6A and 2A. The collection was structured in five sub-populations and modern Argentinian accessions (cluster Q4) which were clearly differentiated. Our study contributes to the understanding of the complexity of Argentinian durum wheat germplasm and to derive future breeding strategies enhancing the use of genetic diversity in a more efficient and targeted way.EEA BarrowFil: Roncallo, Pablo F. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Roncallo, Pablo F. Universidad Nacional del Sur. Departamento de Agronomía. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Larsen, Adelina Olga. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; ArgentinaFil: Achilli, Ana Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Achilli, Ana Laura. Universidad Nacional del Sur. Departamento de Agronomía. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Saint Pierre, Carolina. International Maize and Wheat Improvement Center (CIMMYT); MéxicoFil: Gallo, Cristian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Gallo, Cristian Andrés. Universidad Nacional del Sur. Departamento de Agronomía. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Dreisigacker, Susanne. International Maize and Wheat Improvement Center (CIMMYT); MéxicoFil: Echenique, Carmen Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Echenique, Carmen Viviana. Universidad Nacional del Sur. Departamento de Agronomía. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentin

Genomic Prediction of Gene Bank Wheat Landraces

This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20- TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials

Genetic dissection for head blast resistance in wheat using two mapping populations

Wheat head blast is a dangerous fungal disease in South America and has recently spread to Bangladesh and Zambia, threatening wheat production in those regions. Host resistance as an economical and environment-friendly management strategy has been heavily relied on, and understanding the resistance loci in the wheat genome is very helpful to resistance breeding. In the current study, two recombinant inbred line (RIL) populations, Alondra/Milan (with 296 RILs) and Caninde#2/Milan-S (with 254 RILs and Milan-S being a susceptible variant of Milan), were used for mapping QTL associated with head blast resistance in field experiments. Phenotyping was conducted in Quirusillas and Okinawa, Bolivia, and in Jashore, Bangladesh, during the 2017–18 and 2018–19 cropping cycles. The DArTseq® technology was employed to genotype the lines, along with four STS markers in the 2NS region. A QTL with consistent major effects was mapped on the 2NS/2AS translocation region in both populations, explaining phenotypic variation from 16.7 to 79.4% across experiments. Additional QTL were detected on chromosomes 2DL, 7AL, and 7DS in the Alondra/Milan population, and 2BS, 4AL, 5AS, 5DL, 7AS, and 7AL in the Caninde#2/Milan-S population, all showing phenotypic effects <10%. The results corroborated the important role of the 2NS/2AS translocation on WB resistance and identified a few novel QTL for possible deployment in wheat breeding. The low phenotypic effects of the non-2NS QTL warrantee further investigation for novel QTL with higher and more stable effects against WB, to alleviate the heavy reliance on 2NS-based resistance

Phenotyping mediterranean durum wheat landraces for resistance to Zymoseptoria tritici in Tunisia

Durum wheat landraces have huge potential for the identification of genetic factors valuable for improving resistance to biotic stresses. Tunisia is known as a hot spot for Septoria tritici blotch disease (STB), caused by the fungus Zymoseptoria tritici (Z. tritici). In this context, a collection of 3166 Mediterranean durum wheat landraces were evaluated at the seedling and adult stages for STB resistance in the 2016–2017 cropping season under field conditions in Kodia (Tunisia). Unadapted/susceptible accessions were eliminated to reach the final set of 1059 accessions; this was termed the Med-collection, which comprised accessions from 13 countries and was also screened in the 2018–2019 cropping season. The Med-collection showed high frequency of resistance reactions, among which over 50% showed an immune reaction (HR) at both seedling and adult growth stages. Interestingly, 92% of HR and R accessions maintained their resistance levels across the two years, confirming the highly significant correlation found between seedling-and adult-stage reactions. Plant Height was found to have a negative significant effect on adult-stage resistance, suggesting that either this trait can influence disease severity, or that it can be due to environmental/epidemiological factors. Accessions from Italy showed the highest variability, while those from Portugal, Spain and Tunisia showed the highest levels of resistance at both growth stages, suggesting that the latter accessions may harbor novel QTLs effective for STB resistance

Contamination and oxidative stress biomarkers in estuarine fish following a mine tailing disaster

Background The Rio Doce estuary, in Brazil, was impacted by the deposition of iron mine tailings, caused by the collapse of a dam in 2015. Based on published baseline datasets, the estuary has been experiencing chronic trace metal contamination effects since 2017, with potential bioaccumulation in fishes and human health risks. As metal and metalloid concentrations in aquatic ecosystems pose severe threats to the aquatic biota, we hypothesized that the trace metals in estuarine sediments nearly two years after the disaster would lead to bioaccumulation in demersal fishes and result in the biosynthesis of metal-responsive proteins. Methods We measured As, Cd, Cr, Cu, Fe, Mn, Pb, Se and Zn concentrations in sediment samples in August 2017 and compared to published baseline levels. Also, trace metals (As, Cd, Cr, Cu, Fe, Hg, Mn, Pb, Se and Zn) and protein (metallothionein and reduced glutathione) concentrations were quantified in the liver and muscle tissues of five fish species (Cathorops spixii, Genidens genidens, Eugerres brasilianus, Diapterus rhombeus and Mugil sp.) from the estuary, commonly used as food sources by local populations. Results Our results revealed high trace metal concentrations in estuarine sediments, when compared to published baseline values for the same estuary. The demersal fish species C. spixii and G. genidens had the highest concentrations of As, Cr, Mn, Hg, and Se in both, hepatic and muscle, tissues. Trace metal bioaccumulation in fish was correlated with the biosynthesis of metallothionein and reduced glutathione in both, liver and muscle, tissues, suggesting active physiological responses to contamination sources. The trace metal concentrations determined in fish tissues were also present in the estuarine sediments at the time of this study. Some elements had concentrations above the maximum permissible limits for human consumption in fish muscles (e.g., As, Cr, Mn, Se and Zn), suggesting potential human health risks that require further studies. Our study supports the high biogeochemical mobility of toxic elements between sediments and the bottom-dwelling biota in estuarine ecosystems

Small area analysis methods in an area of limited mapping : exploratory geospatial analysis of firearm injuries in Port-au-Prince, Haiti

Background: The city of Port-au-Prince, Haiti, is experiencing an epidemic of firearm injuries which has resulted in high burdens of morbidity and mortality. Despite this, little scientific literature exists on the topic. Geospatial research could inform stakeholders and aid in the response to the current firearm injury epidemic. However, traditional small-area geospatial methods are difficult to implement in Port-au-Prince, as the area has limited mapping penetration. Objectives of this study were to evaluate the feasibility of geospatial analysis in Port-au-Prince, to seek to understand specific limitations to geospatial research in this context, and to explore the geospatial epidemiology of firearm injuries in patients presenting to the largest public hospital in Port-au-Prince. Results: To overcome limited mapping penetration, multiple data sources were combined. Boundaries of informally developed neighborhoods were estimated from the crowd-sourced platform OpenStreetMap using Thiessen polygons. Population counts were obtained from previously published satellite-derived estimates and aggregated to the neighborhood level. Cases of firearm injuries presenting to the largest public hospital in Port-au-Prince from November 22nd, 2019, through December 31st, 2020, were geocoded and aggregated to the neighborhood level. Cluster analysis was performed using Global Moran’s I testing, local Moran’s I testing, and the SaTScan software. Results demonstrated significant geospatial autocorrelation in the risk of firearm injury within the city. Cluster analysis identified areas of the city with the highest burden of firearm injuries. Conclusions: By utilizing novel methodology in neighborhood estimation and combining multiple data sources, geospatial research was able to be conducted in Port-au-Prince. Geospatial clusters of firearm injuries were identified, and neighborhood level relative-risk estimates were obtained. While access to neighborhoods experiencing the largest burden of firearm injuries remains restricted, these geospatial methods could continue to inform stakeholder response to the growing burden of firearm injuries in Port-au-Prince

Optimizing sparse testing for genomic prediction of plant breeding crops

While sparse testing methods have been proposed by researchers to improve the efficiency of genomic selection (GS) in breeding programs, there are several factors that can hinder this. In this research, we evaluated four methods (M1–M4) for sparse testing allocation of lines to environments under multi-environmental trails for genomic prediction of unobserved lines. The sparse testing methods described in this study are applied in a two-stage analysis to build the genomic training and testing sets in a strategy that allows each location or environment to evaluate only a subset of all genotypes rather than all of them. To ensure a valid implementation, the sparse testing methods presented here require BLUEs (or BLUPs) of the lines to be computed at the first stage using an appropriate experimental design and statistical analyses in each location (or environment). The evaluation of the four cultivar allocation methods to environments of the second stage was done with four data sets (two large and two small) under a multi-trait and uni-trait framework. We found that the multi-trait model produced better genomic prediction (GP) accuracy than the uni-trait model and that methods M3 and M4 were slightly better than methods M1 and M2 for the allocation of lines to environments. Some of the most important findings, however, were that even under a scenario where we used a training-testing relation of 15–85%, the prediction accuracy of the four methods barely decreased. This indicates that genomic sparse testing methods for data sets under these scenarios can save considerable operational and financial resources with only a small loss in precision, which can be shown in our cost-benefit analysis